Machine learing based method and System for determing depression and anxiety of a user

The present disclosure relates to the general idea of the situation that women face. This paradigm entails the investigation and analysis of women's reactions to specific events, as well as the tracking of behaviour patterns through their general thought processes and approaches to problems in...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Shaikh, Asmat Ara, Benhal, Rohan, Patil, Preeti S, Parbat, Tanmayee, Mahajan, Rupali Atul, Sawai, Adv. Pallavi, Shaikh, Mohammed Suhail, Patil, Om Suryakant
Format: Patent
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The present disclosure relates to the general idea of the situation that women face. This paradigm entails the investigation and analysis of women's reactions to specific events, as well as the tracking of behaviour patterns through their general thought processes and approaches to problems in both good and negative ways.The goal of this machine learning interactive platform is to get lonely people to speak up and further define their depression, encouraging them to seek counselling and, if the results are life-threatening, to seek medical help as soon as possible. It also displays a general medical helpline number for suicidal thoughts. receiving an input from a user about personal details including name, weight, age, gender, marital status, dietary habits, financials requesting the user to provide answer to one or more questions relating to health issues assigning points to each of the answers to questions based on a 106 comparison of the answers provided by the user and pre-stored answer to those questions a 108 determining based on the accumulative points if the user falls under mental health issues segment or not providing user with one or more recommendations to overcome mental 110 health related issues if determined to be falling under the mental health issues segment Figure 1 receiving unit202 input unit 204 processing unit206 controlling unit208 recommendation unit 210 Figure 2